The assessment of breast cancer response to neoadjuvant chemotherapy: comparison of magnetic resonance imaging and 18F-fluorodeoxyglucose positron emission tomography

Explainable 3D CNN based on baseline breast DCE-MRI to give an early prediction of pathological complete response to neoadjuvant chemotherapy

BACKGROUND

So far, baseline Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has played a key role for the application of sophisticated artificial intelligence-based models using Convolutional Neural Networks (CNNs) to extract quantitative imaging information as earlier indicators of pathological Complete Response (pCR) achievement in breast cancer patients treated with neoadjuvant chemotherapy (NAC). However, these models did not exploit the DCE-MRI exams in their full geometry as 3D volume but analysed only few individual slices independently, thus neglecting the depth information.

METHOD

This study aimed to develop an explainable 3D CNN, which fulfilled the task of pCR prediction before the beginning of NAC, by leveraging the 3D information of post-contrast baseline breast DCE-MRI exams. Specifically, for each patient, the network took in input a 3D sequence containing the tumor region, which was previously automatically identified along the DCE-MRI exam. A visual explanation of the decision-making process of the network was also provided.

RESULTS

To the best of our knowledge, our proposal is competitive than other models in the field, which made use of imaging data alone, reaching a median AUC value of 81.8%, 95%CI [75.3%; 88.3%], a median accuracy value of 78.7%, 95%CI [74.8%; 82.5%], a median sensitivity value of 69.8%, 95%CI [59.6%; 79.9%] and a median specificity value of 83.3%, 95%CI [82.6%; 84.0%], respectively. The median and CIs were computed according to a 10-fold cross-validation scheme for 5 rounds.

CONCLUSION

Finally, this proposal holds high potential to support clinicians on non-invasively early pursuing or changing patient-centric NAC pathways.

Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy

To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as potential earlier indicators of pathological Complete Response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). However, they work either for sagittal or axial MRI protocols. More flexible AI tools, to be used easily in clinical practice across various institutions in accordance with its own imaging acquisition protocol, are required. Here, we addressed this topic by developing an AI method based on deep learning in giving an early prediction of pCR at various DCE-MRI protocols (axial and sagittal). Sagittal DCE-MRIs refer to 151 patients (42 pCR; 109 non-pCR) from the public I-SPY1 TRIAL database (DB); axial DCE-MRIs are related to 74 patients (22 pCR; 52 non-pCR) from a private DB provided by Istituto Tumori “Giovanni Paolo II” in Bari (Italy). By merging the features extracted from baseline MRIs with some pre-treatment clinical variables, accuracies of 84.4% and 77.3% and AUC values of 80.3% and 78.0% were achieved on the independent tests related to the public DB and the private DB, respectively. Overall, the presented method has shown to be robust regardless of the specific MRI protocol.

Radiomics Analysis of Multi-Phase DCE-MRI in Predicting Tumor Response to Neoadjuvant Therapy in Breast Cancer

Objective: To explore whether the pretreatment dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and radiomics signatures were associated with pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer. Method: A retrospective review of 70 patients with breast invasive carcinomas proved by biopsy between June 2017 and October 2020 (26 patients were pathological complete response, and 44 patients were non-pathological complete response). Within the pre-contrast and five post-contrast dynamic series, a total of 1037 quantitative imaging features were extracted from in each phase. Additionally, the Δfeatures (the difference between the features before and after the comparison) were used for subsequent analysis. The least absolute shrinkage and selection operator (LASSO) regression method was used to select features related to pCR, and then use these features to train multiple machine learning classifiers to predict the probability of pCR for a given patient. The area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the predictive performances of the radiomics model for each of the five phases of time points. Result: Among the five phases, each individual phase performed with AUCs ranging from 0.845 to 0.919 in predicting pCR. The best single phases performance was given by the 3rd phase (AUC = 0.919, sensitivity 0.885, specificity 0.864). 5 of the features have significant differences between pCR and non-pCR groups in each phase, most features reach their maximum or minimum in the 2nd or 3rd phase. Conclusion: The radiomic features extracted from each phase of pre-treatment DCE-MRI possess discriminatory power to predict tumor response.

The development of breast radiology: the Acta Radiologica perspective

The encouraging results of modern breast cancer care builds on tremendous improvements in diagnostics and therapy during the 20th century. Scandinavian countries have made important footprints in the development of breast diagnostics regarding technical development of imaging, cell and tissue sampling methods and, not least, population screening with mammography. The multimodality approach in combination with multidisciplinary clinical work in breast cancer serve as a role model for the management of many cancer types worldwide. The development of breast radiology is well represented in the research published in this journal and this historical review will describe the most important steps.

Contrast enhanced ultrasound quantitative parameters for assessing neoadjuvant chemotherapy response in patients with locally advanced breast cancer

OBJECTIVES

To evaluate the role of contrast-enhanced ultrasound (CEUS) quantitative parameters in predicting neoadjuvant chemotherapy (NACT) response in patients with locally advanced breast cancer (LABC).

METHODS

30 patients with histologically proven LABC scheduled for NACT were recruited. CEUS was performed using a contrast bolus of 4.8 ml and time intensity curves (TICs) were obtained by contrast dynamics software. CEUS quantitative parameters assessed were peak enhancement (PE), time-to-peak (TTP), area under the curve (AUC) and mean transit time (MTT). The parameters were documented on four consecutive instances: before NACT and 3 weeks after each of the three cycles. The gold-standard was pathological response using Miller Payne Score obtained pre NACT and post-surgery.

RESULTS

A decrease in mean values of PE and an increase in mean values of TTP and MTT was observed with each cycle of NACT among responders. Post each cycle of NACT (compared with baseline pre-NACT), there was a statistically significant difference in % change of mean values of PE, TTP and MTT between good responders and poor responders (p-value < 0.05). The diagnostic accuracy of TTP post-third cycle was 87.2% (p = 0.03), and MTT post--second and third cycle was 76.7% (p = 0.004) and 86.7% (p = 0.006) respectively.

CONCLUSION

In responders, a decrease in the tumor vascularity was reflected in the CEUS quantitative parameters as a reduction in PE, and a prolongation in TTP, MTT.

ADVANCES IN KNOWLEDGE

Prediction of NACT response by CEUS has the potential to serve as a diagnostic modality for modification of chemotherapy regimens during ongoing NACT among patients with LABC, thus affecting patient prognosis.

The diagnostic performance of CESM and CE-MRI in evaluating the pathological response to neoadjuvant therapy in breast cancer: a systematic review and meta-analysis

OBJECTIVES

Neoadjuvant chemotherapy (NAC) is an important method for breast cancer treatment. By monitoring its pathological response, the selection of clinical treatment strategies can be guided. In this study, the meta-analysis was used to compare the accuracy of contrast-enhanced MRI (CE-MRI) and contrast-enhanced spectral mammography (CESM) in detecting the pathological response of NAC.

METHODS

Literatures associated to CE-MRI and CESM in the evaluation of pathological response of NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to assess the quality of studies. Pooled sensitivity, specificity, and the area under the SROC curve were calculated to evaluate the diagnostic accuracy of CE-MRI and CESM in monitoring the pathological response of NAC.

RESULTS

There were 24 studies involved, 18 of which only underwent CE-MRI examination, three of which only underwent CESM examination, and three of which underwent both CE-MRI and CESM examination. The pooled sensitivity and specificity of CE-MRI were 0.77 (95%CI, 0.67-0.84) and 0.82 (95%CI, 0.73-0.89), respectively. The pooled sensitivity and specificity of CESM were 0.83 (95%CI, 0.66-0.93) and 0.82 (95%CI, 0.68-0.91), respectively. The AUCs of SROC curve for CE-MRI and CESM were 0.86 and 0.89, respectively.

CONCLUSIONS

Compared to CE-MRI, CESM has equal specificity, greater sensitivity and excellent performance, which may have a brighter prospect in evaluating the pathological response of breast cancer to NAC.

ADVANCES IN KNOWLEDGE

CESM showed equal specificity, greater sensitivity, and excellent performance than CE-MRI.

MRI and PET/CT for evaluation of the pathological response to neoadjuvant chemotherapy in breast cancer: A systematic review and meta-analysis

BACKGROUND

Neoadjuvant chemotherapy (NAC) has become an essential treatment for breast cancer. However, there is still no consensus on the best tool to evaluate pathological response to NAC.

METHODS

Two reviewers systematically searched Cochrane, PubMed, EMBASE, Web of Science, and CBM (last updated in February 2017) for eligible articles. We independently screened and selected studies that conformed to the inclusion criteria and extracted the requisite data. Pooled sensitivity, specificity, and the area under the SROC curve were calculated to estimate the diagnostic accuracy of magnetic resonance imaging (MRI) and positron emission computed tomography (PET/CT). And the relative DOR (RDOR) was used to compare accuracy for levels of the covariable.

RESULTS

Thirteen studies involving 575 patients who underwent MRI and 618 who underwent PET/CT were included in our analysis. The pooled sensitivity and specificity of MRI were 0.88 (95% CI: 0.78-0.94) and 0.69 (95% CI: 0.51-0.83), respectively. The corresponding values for PET/CT were 0.77 (95% CI: 0.58-0.90) and 0.78 (95% CI: 0.63-0.88), respectively. The area under the SROC curve for MRI and PET/CT were 0.88 and 0.84, respectively. And the RDOR = 1.44 (95% CI, 0.46-4.47 P = 0.83).

CONCLUSION

MRI had a higher sensitivity and PET/CT had a higher specificity in predicting the pathologic response after NAC in patients with breast cancer. According to the area under the SROC curve and anatomic discriminative resolution, MRI is the more suitable recommendation for predicting the pathologic response after NAC.

Direct comparison of PET/CT and MRI to predict the pathological response to neoadjuvant chemotherapy in breast cancer: a meta-analysis

Both PET/CT and breast MRI are used to assess pathological complete response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. The aim is to compare the utility of PET/CT and breast MRI by using head-to-head comparative studies. Literature databases were searched prior to July 2016. Eleven studies with a total of 527 patients were included. For PET/CT, the pooled SEN was 0.87 (95% confidence interval (CI): 0.71-0.95) and SPE was 0.85 (95% CI: 0.70-0.93). For MRI, the pooled SEN was 0.79 (95% CI: 0.68-0.87) and SPE was 0.82 (95% CI: 0.72-0.89). In the conventional contrast enhanced (CE)-MRI subgroup, PET/CT outperformed conventional CE-MRI with a higher pooled sensitivity (0.88 (95% CI: 0.71, 0.95) vs. 0.74 (95% CI: 0.60, 0.85), P = 0.018). In the early evaluation subgroup, PET/CT was superior to MRI with a notable higher pooled specificity (0.94 (95% CI: 0.78, 0.98) vs. 0.83 (95% CI: 0.81, 0.87), P = 0.015). The diagnostic performance of MRI is similar to that of PET/CT for the assessment of breast cancer response to NAC. However, PET/CT is more sensitive than conventional CE-MRI and more specific if the second imaging scan is performed before 3 cycles of NAC.

Association of pharmacokinetic and metabolic parameters derived using simultaneous PET/MRI: Initial findings and impact on response evaluation in breast cancer

PURPOSE

To study relationships among pharmacokinetic and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET parameters obtained through simultaneous PET/MRI in breast cancer patients and evaluate their combined potential for response evaluation.

METHODS

The study included 41 breast cancer patients for correlation study and 9 patients (pre and post therapy) for response evaluation. All patients underwent simultaneous PET/MRI with dedicated breast imaging. Pharmacokinetic parameters and PET parameters for tumor were derived using an in- house developed and vendor provided softwares respectively. Relationships between SUV and pharmacokinetic parameters and clinical as well as histopathologic parameters were evaluated using Spearman correlation analysis. Response to chemotherapy was derived as percentage reduction in size and in parameters post therapy.

RESULTS

Significant correlations were observed between SUVmean, max, peak, TLG with K^trans (ρ=0.446, 0.417, 0.491, 0.430; p≤0.01); with Kep(ρ=0.303, ρ=0.315, ρ=0.319; p≤0.05); and with iAUC(ρ=0.401, ρ=0.410, ρ=0.379; p≤0.05, p≤0.01). The ratio of ve/iAUC showed significant negative correlation to SUVmean, max, peak and TLG (ρ=0.420, 0.446, 0.443, 0.426; p≤0.01). Ability of SUV as well as pharmacokinetic parameters to predict response to therapy matched the RECIST criteria in 9 out of 11 lesions in 9 patients. Maximum post therapy quantitative reduction was observed in SUVpeak, TLG and K^trans.

CONCLUSION

Simultaneous PET/MRI enables illustration of close interactions between glucose metabolism and pharmacokinetic parameters in breast cancer patients and potential of their simultaneity in response assessment to therapy.

Role of Magnetic Resonance Imaging in Detection of Pathologic Complete Remission in Breast Cancer Patients Treated With Neoadjuvant Chemotherapy: A Meta-analysis

Pathologic complete remission after neoadjuvant chemotherapy has a role in guiding the management of breast cancer. The present meta-analysis examined the accuracy of contrast-enhanced magnetic resonance imaging (CE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI) in detecting the response to neoadjuvant chemotherapy and compared CE-MRI with ultrasonography, mammography, and positron emission tomography/computed tomography (PET/CT). Medical subject heading terms and related keywords were searched to generate a compilation of eligible studies. The pooled sensitivity, specificity, diagnostic odds ratio, area under summary receiver operating characteristic curve (AUC), and Youden index (Q* index) were used to estimate the diagnostic efficacy of CE-MRI, DW-MRI, ultrasonography, mammography, and PET/CT. A total of 54 studies of CE-MRI and 8 studies of DW-MRI were included. The overall AUC and the Q* index values for CE-MRI and DW-MRI were 0.88 and 0.94 and 0.80 and 0.85, respectively. According to the summary receiver operating characteristic curves, CE-MRI resulted in a higher AUC value and Q* index compared with ultrasonography and mammography but had values similar to those of DW-MRI and PET/CT. CE-MRI accurately assessed pathologic complete remission in specificity, and PET/CT and DW-MRI accurately assessed pathologic complete remission in sensitivity. The present meta-analysis indicates that CE-MRI has high specificity and DW-MRI has high sensitivity in predicting pathologic complete remission after neoadjuvant chemotherapy. CE-MRI is more accurate than ultrasonography or mammography. Additionally, PET/CT is valuable for predicting pathologic complete remission. CE-MRI, combined with PET/CT or DW-MRI, might allow for a more precise assessment of pathologic complete remission.

FDG-PET/CT and MRI for Evaluation of Pathologic Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer: A Meta-Analysis of Diagnostic Accuracy Studies

INTRODUCTION

This study compared the diagnostic test accuracy of magnetic resonance imaging (MRI) with that of (18)F-fluoro-2-glucose-positron emission tomography/computed tomography (FDG-PET/CT) imaging in assessment of response to neoadjuvant chemotherapy (NAC) in breast cancer.

METHODS

A systematic search was performed in PubMed and EMBASE (last updated in June 2015). Studies investigating the performance of MRI and FDG-PET or FDG-PET/CT imaging during or after completion of NAC in patients with histologically proven breast cancer were eligible for inclusion. We considered only studies reporting a direct comparison between these imaging modalities to establish precise summary estimates in the same setting of patients. Pathologic response was considered as the reference standard. Two authors independently screened and selected studies that met the inclusion criteria and extracted the data.

RESULTS

A total of 10 studies were included. The pooled estimates of sensitivity and specificity across all included studies were 0.71 and 0.77 for FDG-PET/CT (n = 535) and 0.88 and 0.55 for MRI (n = 492), respectively. Studies were subgrouped according to the time of therapy assessment. In the intra-NAC setting, FDG-PET/CT imaging outperformed MRI with fairly similar pooled sensitivity (0.91 vs. 0.89) and higher specificity (0.69 vs. 0.42). However, MRI appeared to have higher diagnostic accuracy than FDG-PET/CT imaging when performed after the completion of NAC, with significantly higher sensitivity (0.88 vs. 0.57).

CONCLUSION

Analysis of the available studies of patients with breast cancer indicates that the timing of imaging for NAC-response assessment exerts a major influence on the estimates of diagnostic accuracy. FDG-PET/CT imaging outperformed MRI in intra-NAC assessment, whereas the overall performance of MRI was higher after completion of NAC, before surgery.

IMPLICATIONS FOR PRACTICE

The timing of therapy assessment imaging exerts a major influence on overall estimates of diagnostic accuracy. (18)F-fluoro-2-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) imaging outperformed magnetic resonance imaging (MRI) in intra-neoadjuvant chemotherapy assessment with fairly similar pooled sensitivity and higher specificity. However, MRI appeared to be more accurate than FDG-PET/CT in predicting pathologic response when used in the post-therapy setting.

The Role of (18)F-FDG PET/CT and MRI in Assessing Pathological Complete Response to Neoadjuvant Chemotherapy in Patients with Breast Cancer: A Systematic Review and Meta-Analysis

Purpose. We performed this meta-analysis to determine the utilities of ¹⁸F-FDG PET/CT and MRI in assessing the pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in the same cohort of patients with breast cancer. Methods. Two reviewers systematically searched on PubMed, Scopus, and Springer (from the beginning of 1992 to Aug. 1, 2015) for the eligible articles. Heterogeneity, pooled sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, and the summary receiver operating characteristic (SROC) curve were calculated to estimate the diagnostic efficacy of ¹⁸F-FDG PET/CT and MRI. Results. A total of 6 studies including 382 pathologically confirmed patients were eligible. The pooled sensitivity and specificity of ¹⁸F-FDG PET/CT were 0.86 (95% CI: 0.76–0.93) and 0.72 (95% CI: 0.49–0.87), respectively. Pooled sensitivity and specificity of MRI were 0.65 (95% CI: 0.45–0.80) and 0.88 (95% CI: 0.75–0.95), respectively. The area under the SROC curve of ¹⁸F-FDG PET/CT and MRI was 0.88 and 0.84, respectively. Conclusion. Study indicated that ¹⁸F-FDG PET/CT had a higher sensitivity and MRI had a higher specificity in assessing pCR in breast cancer patients. Therefore, the combined use of these two imaging modalities may have great potential to improve the diagnostic performance in assessing pCR after NAC.

Treatment Response Evaluation of Breast Cancer after Neoadjuvant Chemotherapy and Usefulness of the Imaging Parameters of MRI and PET/CT

This study was aimed to evaluate the ability of imaging parameters measured on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion-weighted MRI (DWI) and positron emission tomography/computed tomography (PET/CT) to serve as response markers in breast cancer after neoadjuvant chemotherapy (NAC). In 20 patients with breast cancer, DCE-MRI and DWI using a 3 T scanner and PET/CT were performed before and after NAC. DCE-MRI was analyzed using an automatic computer-aided detection program (MR-CAD). The response imaging parameters were compared with the pathologic response. The areas under the curve (AUCs) for DCE-MRI using MR-CAD analysis, DWI and PET/CT were 0.77, 0.59 and 0.76, respectively. The combination of all parameters measured by MR-CAD showed the highest diagnostic performance and accuracy (AUC = 0.77, accuracy = 90%). The combined use of the parameters of PET/CT with DCE-MRI or DWI showed a trend toward improved specificity and negative predictive value (100%, 100%, accuracy = 87.5%). The use of DCE-MRI using MR-CAD parameters indicated better diagnostic performance in predicting the final pathological response compared with DWI and PET/CT, although no statistically significant difference was observed. The combined use of PET/CT with DCE-MRI or DWI may improve the specificity for predicting a pathological response.

Role of imaging in neoadjuvant therapy for breast cancer

Neoadjuvant chemotherapy (NAC) involves administration of chemotherapeutic agents to patients with newly diagnosed breast cancer prior to definitive surgical treatment. Assessment of disease response to chemotherapeutic agents in vivo prior to any surgical intervention is necessary as medical oncologists are commonly tailoring or changing therapy during NAC based on response. It can also maximize the pathologic complete response (pCR) rate, resulting in more women undergoing breast conservation rather than mastectomy. Although some studies show a pCR to NAC in only 13-26 % of women, recent studies have shown higher pCR rates, especially for HER2-positive disease treated with targeted anti-HER2 therapy. Thus, accurate imaging tools for quantifying disease response are critical in the evaluation and management of patients undergoing NAC. There is currently no standard imaging method for monitoring response to therapy. Response to therapy tends to vary by tumor subtype and can be accurately assessed on imaging. We review the role of imaging before and after neoadjuvant therapy and discuss the advantages and limitations of currently available modalities, including mammography, ultrasonography, magnetic resonance imaging, and nuclear imaging.

Assessment of tumor response to chemotherapy in patients with breast cancer using (18)F-FLT: a meta-analysis

PURPOSE

To determine the diagnostic performance of 3'-deoxy-3'-(18)F-fluorothymidine positron emission tomography/computed tomography (FLT PET/CT) and FLT PET for evaluating response to chemotherapy in patients with breast cancer.

METHODS

Databases such as PubMed (MEDLINE included) and excerpta medica database (EMBASE), were searched for relevant original articles. The included studies were assessed for methodological quality with quality assessment of diagnosis accuracy studies (QUADAS) score tool. Histopathological analysis and/or clinical and/or radiological follow-up for at least 6 months were used as the reference standard. The data were extracted by two reviewers independently to analyze the sensitivity, specificity, summary receiver operating characteristic (SROC) curve, area under the curve (AUC), and heterogeneity.

RESULTS

The present study analyzed a total of 4 selected articles. The pool sensitivity was 0.773 [95% confidence interval (CI): 0.594-0.900]. The pooled specificity was 0.685 (95% CI: 0.479-0.849) on basis of FEM. The pooled LR+, LR-, and DOR were 2.874 (1.492-5.538), 0.293 (0.146-0.589), and 14.891 (3.238-68.475), respectively. The AUC was 0.8636 (±0.0655), and the Q* index was 0.7942 (±0.0636).

CONCLUSIONS

Our results indicate that (18)F-FLT PET/CT or PET is useful to predict chemotherapy response in breast cancer with reasonable sensitivity, specificity and DOR. However, future larger scale clinical trials will be needed to assess the regimen of (18)F-FLT PET/CT or PET in monitoring the response to chemotherapy in breast cancer patients.

The combination of FDG PET and dynamic contrast-enhanced MRI improves the prediction of disease-free survival in patients with advanced breast cancer after the first cycle of neoadjuvant chemotherapy

PURPOSE

The aim of this study was to investigate the potential of FDG PET/CT and MRI in predicting disease-free survival (DFS) after neoadjuvant chemotherapy (NAC) and surgery in patients with advanced breast cancer.

METHODS

The analysis included 54 women with advanced breast cancer. All patients received three cycles of NAC, underwent curative surgery, and then received three cycles of additional chemotherapy. Before and after the first cycle of NAC, all patients underwent sequential PET/CT and MRI. All patients were analysed using a diverse range of parameters. including maximal standardized uptake value (SUV), percent change in SUV (ΔSUV), initial slope of the enhancement curve (MRslope), apparent diffusion coefficient (ADC), tumour size, change in MRslope (ΔMRslope), change in ADC (ΔADC), change in tumour size (Δsize) and other clinicopathological parameters]. The relationships between covariates and DFS after surgery were analysed using the Kaplan-Meier method and the multivariate Cox proportional hazards model. Time-dependent receiver operating characteristic curves were used to determine the optimal cut-off values of imaging parameters for DFS.

RESULTS

Of the 54 patients, 13 (24 %) experienced recurrence at a median follow-up of 38 months (range 25 - 45 months). Univariate and multivariate analyses showed that a lesser decline in SUV, a lesser decline in MRslope, a lesser increase in ADC, and ER negativity were significantly associated with a poorer DFS (P = 0.0006, ΔSUV threshold -41 %; P = 0.0016, ΔMRslope threshold -6 %; P = 0.011, ΔADC threshold 11 %; and P = 0.0086, ER status, respectively). Patients with a combination of ΔSUV >-41 % and ΔMRslope >-6 % showed a significantly higher recurrence rate (77.8 %) than the remaining of patients (13.3 %, P < 0.0001).

CONCLUSION

Functional parameters of both FDG PET and MRI after the first cycle of NAC are useful for predicting DFS in patients with advanced breast cancer. This approach could lead to an improvement in patient care because ineffective NAC agents could be avoided and more aggressive therapy could be used in high-risk patients.

Predictive value of PET-CT for pathological response in stages II and III breast cancer patients following neoadjuvant chemotherapy with docetaxel

PURPOSE

To prospectively study the value of PET-CT with fluorine-18 fluorodeoxyglucose (FDG) to predict neoadjuvant chemotherapy (NAC) response of locoregional disease of stages II and III breast cancer patients.

MATERIAL AND METHODS

A written informed consent and approval were obtained from the Ethics Committee. PET-CT accuracy in the prediction of pathologic complete response (pCR) after NAC was studied in primary tumors and lymph node metastasis in 43 women (mean age: 50 years: range: 27-71 years) with histologically proven breast cancer between December 2009 and January 2011. PET-CT was performed at baseline and after NAC. SUV(max) percentage changes (ΔSUV(max)) were compared with pathology findings at surgery. Receiver-operator characteristic (ROC) analysis was used to discriminate between locoregional pCR and non-pCR. In patients not achieving pCR, it was investigated if ΔSUV(max) could accurately identify the residual cancer burden (RCB) classes: RCB-I (minimal residual disease (MRD)), RCB-II (moderate RD), and RCB-III (extensive RD).

RESULTS

pCR was obtained in 11 patients (25.6%). Residual disease was found in 32 patients (74.4%): 16 (37.2%) RCB-I, 15 (35.6%) RCB-II and 2 (4.7%) RCB-III. Sensitivity, specificity, and accuracy to predict pCR were 90.9%, 90.6%, and 90.7%, respectively. Specificity was 94.1% in the identification of a subset of patients who had either pCR or MRD.

CONCLUSION

Accuracy of ΔSUV(max) in the locoregional disease of stages II and III breast cancer patients after NAC is high for the identification of pCR cases. Its specificity is potentially sufficient to identify a subgroup of patients who could be managed with conservative surgery.

The current status of positron emission mammography in breast cancer diagnosis

Mammography is currently the standard breast cancer screening procedure, even though it is constrained by low specificity in the detection of malignancy and low sensitivity in women with dense breast tissue. Modern imaging modalities, such as magnetic resonance imaging (MRI), have been developed in an effort to replace or complement mammography, because the early detection of breast cancer is critical for efficient treatment and long-term survival of patients. Nuclear medicine imaging technology has been introduced in the field of oncology with the development of positron emission tomography (PET), positron emission tomography/computed tomography (PET/CT) and, ultimately, positron emission mammography (PEM). PET offers the advantage of precise diagnosis, by measuring metabolism with the use of a radiotracer and identifying changes at the cellular level. PET/CT imaging allows for a more accurate assessment by merging the anatomic localization to the functional image. However, both techniques have not yet been established as diagnostic tools in early breast cancer detection, primarily because of low sensitivity, especially for sub-centimeter and low-grade tumors. PEM, a breast-specific device with increased spatial resolution, has been developed in order to overcome these limitations. It has demonstrated higher detectability than PET/CT and comparable or better sensitivity than MRI. The ability to target the lesions visible in PEM with PEM-guided breast biopsy systems adds to its usability in the early diagnosis of breast cancer. The results from recent studies summarized in this review indicate that PEM may prove to be a useful first-line diagnostic tool, although further evaluation and improvement are required.

18F-FDG PET/CT and PET for evaluation of pathological response to neoadjuvant chemotherapy in breast cancer: a meta-analysis

BACKGROUND

Neoadjuvant chemotherapy is increasingly the treatment for patients with inoperable breast cancer. Considering the side-effects of chemotherapy, there is a need for early evaluating response to neoadjuvant chemotherapy.

PURPOSE

To determinate the diagnostic performance of 18F-fluorodeoxyglucose position emission tomography/computed tomography (FDG PET/CT) and FDG PET for evaluating response to neoadjuvant chemotherapy in patients with breast cancer.

MATERIAL AND METHODS

"PubMed" (MEDLINE included) database, EMBASE, and Cochrane Database of Systematic Reviews were searched for relevant articles. We assessed the methodological quality of included study with Quality Assessment of Diagnosis Accuracy Studies (QUADAS) score tool, and used "Meta-DiSc" statistic software to obtain pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver-operating characteristic (SROC) curve.

RESULTS

Seventeen studies (a total of 781 subjects) met the inclusion criteria. The pooled sensitivity was 0.840 (95% confidence interval [CI] 0.796-0.878). The pooled specificity was 0.713 (95% CI 0.667-0.756). For FDG PET/CT (10 studies included), the pooled sensitivity was 0.847 (95% CI 0.793-0.892), the pooled specificity was 0.661 (95% CI 0.598-0.720). The pooled likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic odds ratio (DOR) were 2.835 (95% CI 1.640-4.900), 0.221 (95% CI 0.160-0.305), and 17.628 (95% CI 7.431-41.818). The area under the SROC curve (AUC) was 0.8934. For FDG PET (7 studies included), the pooled sensitivity and specificity were 0.826 (95% CI 0.741-0.892) and 0.789 (95% CI 0.719-0.849). The pooled LR + , LR-, and DOR were 3.601 (95% CI 2.601-4.986), 0.242 (95% CI 0.157-0.374), and 13.641 (95% CI 7.433-25.030). The AUC was 0.8764.

CONCLUSION

Our results indicate that FDG PET/CT and PET have reasonable sensitivity in evaluating response to neoadjuvant chemotherapy in breast cancer; however, the specificity is relative low. The combination of other imaging methods with FDG PET/CT or PET is recommended.

Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer?

Clinical evidence regarding the value of MRI for therapy responses assessment in breast cancer is increasing. The objective of this study is to compare the diagnostic capability of diffusion-weighted MR imaging (DW-MRI) and contrast-enhanced MR imaging (CE-MRI) to evaluate and predict pathological response in breast cancer patients receiving neoadjuvant chemotherapy (NAC). We performed a meta-analysis of all available studies of the diagnostic performance of DW-MRI or CE-MRI to evaluate and predict pathological response to NAC in patients with breast cancer. We determined sensitivities and specificities across studies, calculated positive and negative likelihood ratios (LR+ and LR-), diagnostic odds ratio (DOR) and constructed summary receiver operating characteristic curves using hierarchical regression models. Methodological quality was assessed by QUADAS tool. Thirty-four studies met the inclusion criteria and involved 1,932 pathologically confirmed patients in total. Methodological quality was relatively high. DW-MRI sensitivity was 0.93 (95 % CI 0.82-0.97) and specificity was 0.82 (95 % CI 0.70-0.90). Overall LR+ was 5.09 (95 % CI 3.09-8.38), LR- was 0.09 (95 % CI 0.04-0.22), and DOR was 55.59 (95 % CI 21.80-141.80). CE-MRI sensitivity was 0.68 (95 % CI 0.57-0.77) and specificity was 0.91 (95 % CI 0.87-0.94). Overall LR+ was 7.48 (95 % CI 5.29-10.57), LR- was 0.36 (95 % CI 0.27-0.48), and DOR was 20.98 (95 % CI 13.24-33.24). Our study confirms that DW-MRI is a high sensitive and CE-MRI is a high specific modality in predicting pathological response to NAC in breast cancer patients. The combined use of DW-MRI and CE-MRI has the potential to improve the diagnostic performance in monitoring NAC. Further large prospective studies are warranted to assess the actual value of this combination in breast cancer preoperative treatment screening.

Is 18F-FDG PET accurate to predict neoadjuvant therapy response in breast cancer? A meta-analysis

Clinical evidence regarding the value of (18)F-FDG PET for therapy responses assessment in breast cancer is increasing. The objective of this study is to evaluate the accuracy of (18)F-FDG PET in predicting responses to neoadjuvant therapies with meta-analysis and explore its optimal regimen for clinical use. Articles in English language relating to the accuracy of (18)F-FDG PET for this utility were retrieved. Methodological quality was assessed by QUADAS tool. Pooled estimation and subgroup analysis data were obtained by statistical analysis. Nineteen studies met the inclusion criteria and involved 920 pathologically confirmed patients in total (mean age 49.8 years, all female). Methodological quality was relatively high. To predict histopathological response in primary breast lesions by PET, the pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic odds ratio were 84% (95% CI, 78-88%), 66% (95% CI, 62-70%), 50% (95% CI, 44-55%), 91% (95% CI, 87-94%), and 11.90 (95% CI, 6.33-22.36), respectively. In regional lymph nodes, sensitivity and NPV of PET were 92% (95% CI, 83-97%) and 88% (95% CI, 76-95%), respectively. Subgroup analysis showed that performing a post-therapy (18)F-FDG PET early (after the 1st or 2nd cycle of chemotherapy) was significantly better than later (accuracy 76% vs. 65%, P = 0.001). Furthermore, the best correlation with pathology was yielded by employing a reduction rate (RR) cutoff value of standardized uptake value between 55 and 65%. (18)F-FDG PET is useful to predict neoadjuvant therapy response in breast cancer. However, the relatively low specificity and PPV still call for caution. It is suggested to perform PET in an earlier course of therapy and use RR cutoff value between 55 and 65%, which might potentially identify non-responders early. However, further prospective studies are warranted to assess this regimen and adequately position PET in treatment management.